• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.7-10
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• 2022

'21년 전국 20개 해상교통관제센터의 선박통항량, 교신량, 관제정보 제공 등 VTS 운영실적 분석 및 사고현황, 원인 분석을 통한 관제서비스 개선방안을 제시하고자 한다. 또한 해양사고 예방기능 강화를 위해 관제사 경험·직관에 의한 관제에서 빅데이터·인공지능(AI) 기반 첨단관제로의 전환, VTS 운영성과에 대한 공신력 확보 및 첨단관제 기술개발에 활용 등을 위한 VTS 통계관리체계 개산 방안에 대해서도 고찰해보았다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.34-41
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• 2009

Recently, information-Ievel of the people has been increased with growing IT cutting-edge technology. There is a trend to combine these achievements with information-technology, ubiquitous technology, and mobile technology in the field of transportation. Along with this trend, a PDA-based traffic accident investigation device was developed. This paper established the evaluation method of feasibility test on the PDA device, and performed qualitative and quantitative evaluation as compared with the current practice (manual investigation). Test results showed that traffic accident investigation using the PDA device was faster and more convenient than manual investigation. It is expected that the reliability of accident investigation will be improved by applying this tool with minor modifications.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.341-344
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• 2006

유고란 도로상에서 교통량의 주기적인 집중에 의한 혼잡과는 구별되는 개념으로 교통사고, 도로보수 그리고 자연재해와 같은 비 반복적인 정체의 상황을 일컫는다. 이러한 유고는 막대한 통행시간이 추가로 발생하고 연료소모, 환경피해 등의 문제가 발생하므로 이러한 교통손실을 최소화하기 위하여 자동유고감지 알고리즘의 개발이 필수적이다. 이를 위하여 현재 다양한 검지기에서 수집된 교통 데이터를 바탕으로 유고를 감지하는 연구가 많이 진행되고 있다. 본 논문에서는 각종 유고 상황을 인지하여 제2의 사고를 예방할 수 있는 효율적인 유고감지 알고리즘을 개발하기 위하여 퍼지논리와 패턴을 함께 사용하였다. 먼저 퍼지논리와 패턴에 사용되는 데이터는 루프 검지기에서 5분 마다 수집된 교통정보(교통량, 점유율, 속도)를 이용하였다. 교통정보를 이용하여 구축된 요일 및 시간대별 패턴과 함께 퍼지논리를 이용하여 도출된 유고 소속도를 가지고 유고를 감지하였다.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.3-9
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• 2015

Since changes in land use in urban space cause traffic volume and it is closely related to traffic accidents. Therefore, an analysis on the causes of traffic accidents is judged to be an essential factor to establish the measure to reduce traffic accidents. In this regard, the analysis was conducted on the clustering by using the nearest neighbor indexes with regard to the occurrence frequencies of commercial and residential zone based on traffic accident data of the past five years (2009-2013) with the target of local small-medium sized city, Jinju-si. The analysis results, obtained in this study, are as follows: the occurrence frequency of traffic accidents was the highest in spring and the lowest in winter respectively. The clustering of traffic accident occurrence at nighttime was stronger than at daytime. In addition, terms of the analysis on the clustering of traffic accident according to land use, changes according to the seasons was not significant in commercial areas, while clustering density in winter tended to become significantly lower in residential areas. The analysis results of traffic accident types showed that the side-right angle collision of cars was the highest in frequency occurrence, and widespread in both commercial areas and residential areas. These results can provide us with important information to identify the occurrence pattern of traffic accidents in the structure of urban space, and it is expected that they will be appropriately utilized to establish measures to reduce traffic accidents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.1
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• pp.49-56
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• 2021

The purpose of this study is to develop a methodology to select a cluster of night traffic accidents using CRP (Continuous Risk Profile) analysis. the other purpose of this study is to present the characteristics of the traffic accident cluster section selected at night using CRP analysis. The CRP analysis was performed considering traffic volume of target routes through traffic accident data. In addition, variables were set according to the freeway sections. the method of subtracting the daytime CRP from the nighttime CRP was used to analyze the nighttime traffic accident. As a result, Using the CRP analysis, the sections of hotspot were identified and plotted based on traffic accidents. Also, the sections where traffic accidents are frequent were those where IC or Tunnels were installed, and there was a deviation from the general section. In conclusion, CRP analysis could be used to calculate the frequent section of specialized traffic accidents at night, and it was selected as a point in need of improvement due to the frequent occurrence of specialized traffic accidents at night in the section where IC or tunnel facilities are installed. In addition, it is inferred that the number of specialized traffic accidents at night in the section where IC or tunnel facilities are installed is a factor in the problem of night visibility due to lighting facilities.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.106-106
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• 2017

우리나라는 현재 재난의 유형을 자연재난과 사회재난으로 구분하여 관리하고 있다. 하지만 최근 재난 사고 사례를 살펴보면 단일재난으로 인한 피해보다 자연재난이 발생한 이후 사회재난으로 재난이 전파되는 복합재난의 형태가 종종 나타나고 있다. 복합재난은 단일 재난에 의한 피해(인적, 물적) 보다 크게 나타나고 복합재난의 발생원인 및 전파과정을 분석하기 어려워 이에 대한 다각적인 분석과 동시에 재난상호간의 연관성을 도출하는 연구가 필요한 시점이다. 과거 재난사고정보를 분석하는 연구는 일반적인 통계기법을 활용한 분석에 머물러 있으며 수집된 재난사고사례가 많지 않아 분석에 신뢰성을 보장할 수 없었다. 이에 본 연구에서는 복잡하게 나타나는 재난 사고를 분석하기 위하여 최근 각광받고 있는 인공지능 분석기법을 연구에 고려하였다. 본 연구의 과정은, 첫째로 재난사고정보 분석에 인공지능을 활용한 사례를 조사하고 여타 연구분야에서 적용되고 있는 인공지능 분석기술을 재난사고정보 분석에 활용할 수 있는 방안을 모색하였다. 둘째로 수집가능 한 재난사고정보를 수집하고 인공지능 모형에 적용가능 한 형태로 변환하는 과정을 수행하였다. 셋째로 변환된 재난사고정보를 대표적인 인공지능 알고리즘을 활용하여 다양한 질문(목적)에 부합하는 재난사고정보 분석모형을 구축하고자 하였다. 마지막으로 다양한 인공지능 알고리즘을 적용한 모형의 신뢰성을 비교하였으며 이를 통하여 재난사고정보 분석에 적용가능 하며 질문(목적)에 부합하는 최적 인공지능 알고리즘을 도출하고자 하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.20-37
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• 2023

Although traffic signal installations are continuously expanding, the effect of preventing traffic accidents remains unverified. Totally, 7,045 traffic accident data (such as signal violations) registered with TCS were manually searched for a 7-year period from 2013 to 2019 for 1,602 traffic signals in Daejeon Metropolitan City. The top 20 traffic accident intersections were identified, the traffic accident investigation records and field maps were viewed to compare the driving direction and signal phase of the violated vehicle, and the cause of the traffic accident was divided into insufficient signal operation design (operation) and driver negligence (intentional). Results of the analysis revealed that 75% of traffic accidents occurred in thru-left-turn traffic signals and overlap; moreover, extending the yellow time or operating all red signals due to countermeasures against traffic accidents occurring in yellow signals resulted in reduced traffic accidents. Data indicated that Permissive Left Turn requires improvement with the signal operation. In addition, since The Korean National Police Agency is not computerized for traffic accident sites and signal-related data, the lack of manpower necessitates improvement and utilization of TCS when establishing traffic accident prevention measures. It is believed that it will contribute to signal operation by analyzing vast amounts of data collected in the field and presenting improvement measures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.15-31
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• 2024

The characteristics of elderly traffic accidents were identified by reflecting the situation of the elderly population in Korea, which is entering an ultra-aging society, and the relationship between independent and dependent variables was analyzed by classifying traffic accidents of serious or higher and traffic accidents of minor or lower in elderly pedestrian traffic accidents using binomial variables. Data collection, processing, and variable selection were performed by acquiring data from the elderly pedestrian traffic accident analysis system (TAAS) for the past 10 years (from 13 to 22 years), and basic statistics and analysis by accident factors were performed. A total of 15 influencing variables were derived by applying the logistic regression model, and the influencing variables that have the greatest influence on the probability of a traffic accident involving severe or higher elderly pedestrians were derived. After that, statistical tests were performed to analyze the suitability of the logistic model, and a method for predicting the probability of a traffic accident according to the construction of a prediction model was presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.521-523
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• 2021

As the invention of automobiles and construction of roads for vehicles began, the occurrence of traffic accidents began to increase. Accordingly, efforts were made to prevent traffic accidents by changing the road construction method and using signal systems such as traffic lights, but even today, numerous human and property damages have occurred due to traffic accidents caused by freezing of the road due to bad weather. In this paper, in order to reduce traffic accidents due to road freezing, we propose a method of transferring the ice detection information obtained by deep learning of infrared wavelength data obtained using an infrared camera to the vehicle's navigation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.827-833
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• 2022

This study aims to prevent secondary traffic accidents with high severity by overcoming the limitations of existing traffic information collection systems through analysis of traffic information collection detectors and various algorithms used to detect unexpected situations. In other words, this study is meaningful present that analyzing the 'unexpected situation that causes secondary traffic accidents' and 'Existing traffic information collection system' accordingly presenting a solution that can preemptively prevent secondary traffic accidents, intelligent traffic information collection system that enables accurate information collection on all sections of the road. As a result of the experiment, the reliability of data transmission reached 97% based on 95%, the data transmission speed averaged 209ms based on 1000ms, and the network failover time achieved targets of 50sec based on 120sec.